Halifax, Nova Scotia, Canada
I help immigrants and career-switchers land analyst roles—without burning out on certificates. By day I build decision-grade analytics (currently at Autodesk). By night I run Data Career Compass, where we treat your job search like a product launch: Market → Positioning → Portfolio → Distribution → Interviews. My POV: Most candidates try to add more tools. Winners learn to package their value. Your portfolio isn’t a gallery; it’s a sales page for your judgment. Receipts: → Professionals land interviews by aligning projects to business outcomes (not toy datasets). → My frameworks have been used across finance, tech, and education to translate experience into results. → Built data products and controls in regulated environments (RBC Capital Markets) that leaders rely on daily. What you’ll get here: → Weekly breakdowns of real projects (SQL, Python, dbt, DuckDB, Looker/Tableau/Power BI). → Storytelling patterns that turn insights into action. → Templates that remove friction: portfolio briefs, stakeholder one-pagers, interview scorecards. Coming June: I’m launching a coaching program designed for mid-level and senior professionals ready to transition into analytics. This isn’t an entry-level bootcamp—it’s a career accelerator that helps you reposition your existing experience, communicate business value, and step confidently into data-driven roles. Work with me: ↳ Cohorts + 1:1 coaching → DM “HIRED” ↳ April program for mid/senior professionals → DM “JUNE” for early access ↳ Guest workshops for teams and communities → DM “WORKSHOP” I build analysts who think like product managers and communicate like consultants.
Working on cutting edge technology - Augmented and Virtual Reality (XR) - for Architecture, Engineering, & Construction (AEC) industry and leveraging data to improve product features and understand customer usage patterns. --- - Built FY26 OKR analytics for Commercial MAU and ARR, defining robust cohort logic and executive-ready semantic layers to size and track product feature impact. - Engineered the Commercial MAU backend with 3 user cohorts, MoM growth, and rigorous dbt tests, moving beyond insights to deliver a durable data product for leadership visibility. - Designed and shipped retention and account expansion dashboards, uncovering root-cause gaps in feature adoption and adding clear visibility into renewal and growth opportunities to directly influence the product roadmap.
Helping career professional find meaningful opportunities in data analytics and achieve their dream career goals.
- Lead the requirements gathering and creation of data quality rules for a new regulatory initiative (T+1). - Manage 2 contract workers in drafting requirements, reviewing data lineage and creating be-spoke data quality rules across multiple quality dimensions. - Built a Tableau report all data quality controls created with meta-data on schema and other useful data elements to help reduce the time in the drafting of new data controls by 20% - Built a Python script to Extract Deeply Nested JSON from S3 and Tranform into a CSV format for easy processing and analysis. (Avg size of data set is 1.2GB across 10 different instances with over 10 different critical data elements)
• Resolved a data quality issue of missing maturity dates on outstanding loans with a material impact of 122 billion USD. • Collaborated with finance and regulatory reporting stakeholders to implement business requirements, resulting in a 25% increase in data quality and adherence to compliance guidelines as part of an enhanced enterprise data governance framework. • Utilized Tableau to create an intuitive schema and data quality report, leading to a 35% enhancement in departmental rule design efficiency at RBC Capital Markets. • Engineered data pipeline processes using Airflow and Python, reducing data processing times by 30% for faster insights delivery and improved efficiency in strategic decision-making. • Collaborated with Regulatory Reporting and Finance IT stakeholders to enhance data quality and efficiency using DBT, resulting in a 25% reduction in data-related errors. • Developed SQL data models on a cloud data warehouse and administered a Dremio data lake, handling over 10TB of data.
- Built self-serve Looker dashboards to support product and business stakeholders, reducing data team dependency by 20% through scalable data models and reliable data pipelines, showcasing pipeline development expertise and application of data insights for infrastructure. - Led a Looker project supporting Finance and Operations teams that increased monthly sales targets by 25% by designing a sales forecast dashboard to rapidly inform Sales and Go-To-Market teams, emphasizing the go-to-market strategy and scalability. - Boosted data accuracy and retrieval speed by 25% using dbt and optimized Snowflake schemas for better data reliability and scalable data solutions, focusing on orchestration tools and maintenance, and leveraging big-picture thinking in analytics. - Proactively identified trends in user behavior, providing insights that informed product development, resulting in a 15% improvement in user experience metrics and better alignment with business requirements through quantitative analysis and data manipulation.